4 papers · 1 filter
Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins
Rei Tamaru, Pei Li, Bin Ran
Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these representations fail to cap…
CrashSight: A Phase-Aware, Infrastructure-Centric Video Benchmark for Traffic Crash Scene Understanding and Reasoning
Rui Gan, Junyi Ma, Pei Li +4
Cooperative autonomous driving requires traffic scene understanding from both vehicle and infrastructure perspectives. While vision-language models (VLMs) show strong general reaso…
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection
Rei Tamaru, Pei Li, Bin Ran
Digital Twins (DT) have the potential to transform traffic management and operations by creating dynamic, virtual representations of transportation systems that sense conditions, a…
Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information
Rei Tamaru, Pei Li, Bin Ran
Pedestrian trajectory prediction is essential for various applications in active traffic management, urban planning, traffic control, crowd management, and autonomous driving, aimi…